A custom KernelManager class could check the number of running kernels and
raise a 400 error if too many are already running.

On Sun, Apr 23, 2017 at 12:07 PM, Pratham Maliwad <[email protected]
> wrote:

> Hi,
>
> I am using Jupyter Hub v0.7.2, JupyterNotebook v4.2.0 and Jupyter Lab
> V0.16.2.
> We have multiple kernels - Python 3.5, PySpark 1.6.1, etc.
>
> Users are opening too many notebooks simultaneously and not closing the
> notebook or kernel at the end of their work.
>
> Has any implemented a solution to control number of kernels/user or
> notebook/user? What's the best way possible way to control number of
>  kernels/user or notebook/user?
>
> --
> Thanks
>
> Pratham
>
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